Bubble detection method and device and analyzer
By collecting and analyzing the capacitance signal of the liquid level detection module, we can determine whether there are bubbles in the sample, which solves the problems of inconvenience and high cost of traditional methods, and achieves convenient and efficient bubble detection.
Patent Information
- Application Number
- CN202411995543.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-31
- Publication Date
- 2025-04-25
AI Technical Summary
Traditional bubble detection methods require targeted sensors for different samples and sample tubes, which is inconvenient to use and increases the manufacturing cost of the equipment.
By collecting the capacitance signal of the liquid level detection module during the sampling process, calculate the change trend of the capacitance signal, determine the characteristic value of the capacitance signal, and determine whether there are bubbles based on the characteristic value and the preset alarm threshold.
The convenience and efficiency of bubble detection are achieved without additional sensors, reducing the cost of use and improving detection reliability.
Smart Images
Figure CN119881028A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of medical device technology, and in particular to a bubble detection method, device and analyzer. Background Art
[0002] Medical devices include a variety of in vitro diagnostic testing equipment. During the sampling operation of these testing equipment, bubbles will be generated above the liquid surface due to shaking or other vibrations of the sample object. In the case of bubbles, the sample suction process will trigger the sensor to detect the liquid surface in advance due to the presence of bubbles, resulting in abnormal sampling. Therefore, it is necessary to detect bubbles.
[0003] The traditional method of detecting bubbles is to add an infrared sensor to the sample suction device and measure the relationship between the output voltage and the light intensity. When there are bubbles in the sample tube, the absorption and reflection characteristics of different media to light will cause the light intensity received by the photosensitive element to change, thereby causing fluctuations in the output voltage. Based on this principle, different media in the pipeline can be distinguished and bubbles can be detected. However, due to the different detection positions of different sample tubes, different sample optical properties and medium conditions, etc., this detection method requires the targeted setting of sensors for different samples and different sample tubes, which is inconvenient to use and also increases the manufacturing cost of the equipment. Summary of the invention
[0004] Based on this, it is necessary to provide a bubble detection method, device and analyzer that can improve the convenience of detection in order to address the technical problems of the inconvenience of using traditional bubble detection methods.
[0005] In a first aspect, the present application provides a bubble detection method, the method comprising:
[0006] Collecting a capacitance signal of a liquid level detection module during the sample suction process; the liquid level detection module is used to detect the liquid level of the sample;
[0007] Calculating the variation trend of the capacitance signal to obtain a capacitance variation trend signal;
[0008] Determining a capacitance signal characteristic value according to the capacitance change trend signal and a preset signal amplitude;
[0009] Whether bubbles exist in the sample is determined according to the characteristic value of the capacitance signal and a preset alarm threshold.
[0010] In one embodiment, after collecting the capacitance signal of the liquid level detection module during the sample suction process and before calculating the change trend of the capacitance signal to obtain the capacitance change trend signal, the method further includes:
[0011] In the capacitance signal, a capacitance signal of a baseline segment is intercepted; the capacitance signal of the baseline segment includes a capacitance signal between a liquid level detection trigger position and a sample suction needle starting position;
[0012] The capacitance signal is updated using the capacitance signal of the baseline segment.
[0013] In one embodiment, calculating the variation trend of the capacitance signal to obtain the capacitance variation trend signal includes:
[0014] Perform differential signal calculation on the capacitance signal to obtain the capacitance change trend signal.
[0015] In one embodiment, performing differential signal calculation on the capacitance signal to obtain the capacitance change trend signal includes:
[0016] After filtering the capacitance signal, performing differential signal calculation to obtain a differential signal;
[0017] After filtering the differential signal, the capacitance change trend signal is obtained.
[0018] In one embodiment, determining the capacitance signal characteristic value according to the capacitance change trend signal and the preset signal amplitude includes:
[0019] The capacitance signal characteristic value is determined according to a capacitance change trend signal whose amplitude is smaller than the preset signal amplitude.
[0020] In one embodiment, determining the capacitance signal characteristic value according to the capacitance change trend signal having an amplitude less than the preset signal amplitude includes:
[0021] When the amplitude of the current capacitance change trend signal is smaller than the preset signal amplitude, and the amplitudes of a preset number of capacitance change trend signals after the current capacitance change trend signal are all smaller than the preset signal amplitude, the capacitance signal characteristic value is determined according to the current capacitance change trend signal.
[0022] In one embodiment, determining the capacitance signal characteristic value according to the current capacitance change trend signal includes:
[0023] The sampling quantity corresponding to the current capacitance change trend signal is determined as the capacitance signal characteristic value.
[0024] In one embodiment, determining whether bubbles exist in the sample according to the characteristic value of the capacitance signal and a preset alarm threshold comprises:
[0025] When the characteristic value of the capacitance signal is greater than the preset alarm threshold, determining that bubbles exist in the sample;
[0026] When the characteristic value of the capacitance signal is less than or equal to the preset alarm threshold, it is determined that no bubbles exist in the sample.
[0027] In a second aspect, the present application further provides a bubble detection device, the device comprising:
[0028] A signal acquisition module, used to collect the capacitance signal of the liquid level detection module during the sample aspiration process; the liquid level detection module is used to detect the liquid level of the sample;
[0029] A signal change analysis module, used to calculate the change trend of the capacitance signal and obtain a capacitance change trend signal;
[0030] A signal characteristic determination module, used to determine a capacitance signal characteristic value according to the capacitance change trend signal and a preset signal amplitude;
[0031] The judgment module is used to determine whether there are bubbles in the sample according to the characteristic value of the capacitance signal and a preset alarm threshold.
[0032] In a third aspect, the present application further provides an analyzer, comprising a liquid level detection module and a controller, wherein the controller is connected to the liquid level detection module;
[0033] The liquid level detection module is used to detect the liquid level of the sample, generate a capacitance signal and send it to the controller, and the controller is used to perform bubble detection according to the method of any of the above embodiments.
[0034] The above-mentioned bubble detection method, device and analyzer collect the capacitance signal generated by the liquid surface of the sample during the sample absorption process, and then calculate the change trend of the capacitance signal to obtain the capacitance change trend signal, determine the capacitance signal characteristic value based on the capacitance change trend signal and the preset signal amplitude, and determine whether there are bubbles in the sample based on the capacitance signal characteristic value and the preset alarm threshold. Therefore, bubble detection can be achieved through the existing liquid level detection module without the need to set up additional sensors, which reduces the cost of use and improves the convenience of detection. By effectively detecting bubbles, the probability of erroneous detection results is effectively reduced, and the detection reliability is improved. BRIEF DESCRIPTION OF THE DRAWINGS
[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0036] Figure 1 A schematic diagram of a flow chart of a bubble detection method in one embodiment;
[0037] Figure 2 is a schematic structural diagram of a liquid level detection module in one embodiment;
[0038] Figure 3 is a schematic flow chart of a bubble detection method in another embodiment;
[0039] Figure 4 is a schematic flow chart of a bubble detection method in another embodiment;
[0040] Figure 5 It is a flowchart of the steps of performing differential signal calculation on a capacitance signal to obtain a capacitance change trend signal in one embodiment;
[0041] Figure 6 is a schematic flow chart of a bubble detection method in another embodiment;
[0042] Figure 7 is a schematic flow chart of a bubble detection method in another embodiment;
[0043] Figure 8 It is a flowchart of a step of determining whether there are bubbles in a sample according to a characteristic value of a capacitance signal and a preset alarm threshold in one embodiment;
[0044] Fig. 9 is a detailed schematic diagram of a bubble detection method in another embodiment;
[0045] Fig.10 is a waveform diagram of a capacitance curve S1 in one embodiment;
[0046] Fig.11 is a waveform diagram of a capacitance curve S2 in one embodiment;
[0047] Fig.12 is a waveform diagram of a capacitance curve S3 in one embodiment;
[0048] Fig.13 is a waveform diagram of a capacitance curve S4 in one embodiment;
[0049] Fig.14 4 is a structural block diagram of a bubble detection device in one embodiment. DETAILED DESCRIPTION
[0050] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.
[0051] The bubble detection method provided in the embodiment of the present application is used to detect bubbles in a sample, and can be specifically used to detect bubbles at the liquid surface of the sample. The bubble detection method can be applied in an analyzer, and the sample is firstly detected for bubbles when or before the analyzer samples the sample. Alternatively, the bubble detection method can also be applied in other devices, which can be determined according to actual needs.
[0052] The bubble detection method can be executed by a controller in the analyzer, or by a terminal or server connected to the analyzer. The terminal can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The server can be implemented as an independent server or a server cluster consisting of multiple servers.
[0053] It should be noted that the sample of the present application is not limited to the sample to be tested, but may also be other liquids entering the analyzer, such as reagents used in the analyzer, or a mixture of reagents and the sample to be tested.
[0054] In an exemplary embodiment, Figure 1 As shown, a bubble detection method is provided, which is described by taking the method applied to a controller in an analyzer as an example, and includes the following steps 102 to 108. Among them:
[0055] Step 102, collecting the capacitance signal of the liquid level detection module during the sample suction process.
[0056] The liquid level detection module is used to detect the liquid level of the sample. Figure 2 As shown, the liquid level detection module includes a detection needle 212 and a liquid level detection plate 214, and the detection needle 212 is connected to the liquid level detection plate 214. The detection needle 212 is connected to a motor and driven by the motor.
[0057] When the probe needle 212 contacts the liquid surface of the sample or the bubbles on the liquid surface, the capacitance value of the probe needle 212 changes, causing its impedance to change. The impedance change is further processed by the liquid level detection board 214, and the obtained signal amplitude changes accordingly to obtain the final capacitance signal.
[0058] The controller may be connected to the liquid level detection board 214 of the liquid level detection module to obtain a capacitance signal of the liquid level detection module.
[0059] The sample suction process is controlled by a motor, and the motor drives the detection needle 212 to move. The sample suction process includes four steps: needle lifting, needle moving, needle lowering, and needle lifting, and each step has a corresponding flag signal as a trigger basis.
[0060] When the motor drives the detection needle to move, specifically in the four steps of needle lifting, needle moving, needle lowering and needle lifting, the controller obtains a signal from the liquid level detection plate 214 of the liquid level detection module to obtain a capacitance signal of the liquid level detection module.
[0061] Step 104, calculating the variation trend of the capacitance signal to obtain a capacitance variation trend signal.
[0062] The capacitance signal includes multiple capacitance signals collected in time sequence. By calculating the change trends of the multiple capacitance signals, a capacitance change trend signal can be obtained. The capacitance change trend signal can reflect the change of the capacitance signal.
[0063] There is not only one way to calculate the variation trend of the capacitance signal. For example, capacitance signals collected at different times may be compared to obtain a capacitance variation trend signal.
[0064] Step 106: Determine a capacitance signal characteristic value according to the capacitance change trend signal and a preset signal amplitude.
[0065] Among them, the value of the preset signal amplitude is not unique, and can be a value set according to demand or an empirical value. The preset signal amplitude can characterize the stable state of the signal. For example, when the amplitude of the signal is less than the preset signal amplitude, it means that the amplitude of the signal is small, the fluctuation is small, and the signal is relatively stable. When the amplitude of the signal is greater than the preset signal amplitude, it means that the amplitude of the signal is large, the fluctuation is large, and the signal is not stable enough.
[0066] The method of determining the characteristic value of the capacitance signal according to the capacitance change trend signal and the preset signal amplitude is not unique. Exemplarily, the characteristic value of the capacitance signal is determined according to the capacitance change trend signal in a stable state. Then, when the amplitude of the capacitance change trend signal is less than the preset signal amplitude, the characteristic value of the capacitance signal can be determined according to the capacitance change trend signal. It can be understood that in other embodiments, the characteristic value of the capacitance signal can also be determined according to other methods, which will not be repeated here.
[0067] Step 108: Determine whether there are bubbles in the sample based on the characteristic value of the capacitance signal and the preset alarm threshold.
[0068] The characteristic value of the capacitance signal can reflect the difference between a normal signal and an abnormal signal. When the liquid level is detected, the capacitance signal is a normal signal, and when bubbles are detected, the capacitance signal is an abnormal signal. The characteristic value of the capacitance signal corresponding to the normal signal is different from the characteristic value of the capacitance signal corresponding to the abnormal signal. Therefore, by analyzing the characteristic value of the capacitance signal, it is possible to determine whether the signal is abnormal, and thus determine whether there are bubbles in the sample.
[0069] There is no unique way to determine whether there are bubbles in the sample based on the characteristic value of the capacitance signal. In this embodiment, whether there are bubbles in the sample is determined based on the characteristic value of the capacitance signal and the preset alarm threshold. The preset alarm threshold can be a value determined by a large amount of experimental data. Specifically, whether there are bubbles in the sample can be determined based on the size relationship between the characteristic value of the capacitance signal and the preset alarm threshold.
[0070] In the above-mentioned bubble detection method, during the process of collecting sample suction, after the liquid level detection module detects the capacitance signal generated by the liquid level of the sample, it calculates the change trend of the capacitance signal to obtain the capacitance change trend signal, determines the capacitance signal characteristic value based on the capacitance change trend signal and the preset signal amplitude, and determines whether there are bubbles in the sample based on the capacitance signal characteristic value and the preset alarm threshold. Therefore, bubble detection can be achieved through the existing liquid level detection module without the need to set up additional sensors, which reduces the cost of use and improves the convenience of detection. By effectively detecting bubbles, the probability of erroneous detection results is effectively reduced, and the detection reliability is improved.
[0071] In an exemplary embodiment, Figure 3 As shown, after step 102 and before step 104 , the bubble detection method further includes steps 302 and 304 .
[0072] Step 302: intercept the capacitance signal of the baseline segment from the capacitance signal.
[0073] The capacitance signal of the baseline segment includes the capacitance signal between the liquid level detection trigger position and the sample suction needle starting position.
[0074] Since the whole process of sample absorption is relatively long, the number of collected capacitance signals is large, and some capacitance signals do not change much. Therefore, after collecting the capacitance signals in the process of sample absorption, some capacitance signals of all capacitance signals are intercepted for subsequent analysis, and the capacitance signals that are not intercepted are no longer used, which can reduce the amount of data and improve the detection efficiency.
[0075] In this step, the capacitance signal of the baseline segment is intercepted from the capacitance signal. Among them, the capacitance signal of the baseline segment includes the capacitance signal between the liquid level detection trigger position and the sample suction needle starting position. The baseline segment is a specific interval, and the specific interval can be (t0, t1). Each step in the sample suction process has a corresponding flag signal as a trigger basis. Among them, t0 is the signal point position returned after the liquid level detection module detects the liquid level, and t1 is the signal point position when the detection needle starts to end the detection during the entire detection process.
[0076] Step 304: update the capacitance signal of the baseline segment.
[0077] After the capacitance signal of the baseline segment is obtained, the capacitance signal of the baseline segment is used to update the capacitance signal. The subsequent steps that require the use of the capacitance signal are all replaced by the capacitance signal of the baseline segment.
[0078] In this embodiment, in the capacitance signal, the capacitance signal of the baseline segment is intercepted, and the capacitance signal of the baseline segment is updated. Updating the capacitance signal of the baseline segment can reduce the amount of data to be processed while retaining the feature data.
[0079] In an exemplary embodiment, Figure 4 As shown, step 104 includes step 404: performing differential signal calculation on the capacitance signal to obtain a capacitance change trend signal.
[0080] The specific process of performing differential signal calculation on the capacitance signal includes: calculating the difference between the current signal and the previous signal in the capacitance signal to obtain a differential signal. Performing differential signal calculation on multiple capacitance signals can obtain multiple differential signals to form a differential signal group, which can be used as a capacitance change trend signal.
[0081] In this embodiment, differential signal calculation is performed on the capacitance signal to complete the calculation of the signal change trend, so that the change trend is intuitive and prepares for the next step of calculation.
[0082] Furthermore, in an exemplary embodiment, Figure 5 As shown, step 404 includes step 502 and step 504 .
[0083] Step 502: After filtering the capacitance signal, perform differential signal calculation to obtain a differential signal.
[0084] In this step, after filtering the capacitance signal, differential signal calculation is performed, which can remove the original signal noise in the capacitance signal and eliminate the influence of burrs and miscellaneous peaks on the next step of calculation. The signal obtained after differential signal calculation can become a differential signal.
[0085] Step 504: Filter the differential signal to obtain a capacitance change trend signal.
[0086] After the differential signal is obtained, the differential signal is filtered to remove the noise of the differential signal and eliminate the influence of burrs and miscellaneous peaks on the next step of calculation. Then, the capacitance change trend signal is obtained.
[0087] In this embodiment, through two filtering processes, the noise in the signal can be well removed and the quality of the capacitance change trend signal can be improved.
[0088] In an exemplary embodiment, Figure 6 As shown, step 106 includes step 606: determining a capacitance signal characteristic value according to a capacitance change trend signal whose amplitude is less than a preset signal amplitude.
[0089] Among them, when the amplitude of the signal is less than the preset signal amplitude, it means that the amplitude of the signal is small, the fluctuation is small, and the signal is relatively stable.
[0090] When the liquid level is detected, the capacitance signal is a normal signal, and when bubbles are detected, the capacitance signal is an abnormal signal. Through the collection and analysis of a large amount of actual data, it can be found that: compared with normal signals, abnormal signals take longer to reach a stable signal value, and the abnormal data reaches a stable state, and the interference is the fluctuation of the signal amplitude. Therefore, based on the capacitance change trend signal with an amplitude less than the preset signal amplitude, the characteristic value of the capacitance signal can be determined.
[0091] In this embodiment, the capacitance signal characteristic value is determined based on the capacitance change trend signal whose amplitude is less than the preset signal amplitude. The obtained capacitance signal characteristic value can reflect the difference between normal signals and abnormal signals, which is convenient for subsequent bubble detection.
[0092] In an exemplary embodiment, Figure 7 As shown, step 606 includes step 706: when the amplitude of the current capacitance change trend signal is less than the preset signal amplitude, and the amplitudes of a preset number of capacitance change trend signals after the current capacitance change trend signal are all less than the preset signal amplitude, determine the capacitance signal characteristic value according to the current capacitance change trend signal.
[0093] The specific value of the preset number may be an empirical value obtained from experiments, or a value set according to demand.
[0094] Since the amplitude fluctuation may exist in multiple stages, a single amplitude fluctuation may cause the detection to be triggered in advance. Therefore, in this embodiment, whether the amplitudes of a preset number of capacitance change trend signals after the current capacitance change trend signal are all less than the preset signal amplitude is continued to be used as a judgment basis, which can eliminate the influence of multiple fluctuations, thereby improving the accuracy of the determined capacitance signal characteristic value.
[0095] In an exemplary embodiment, in step 706, the step of determining the characteristic value of the capacitance signal according to the current capacitance change trend signal includes the step of: determining the number of samples corresponding to the current capacitance change trend signal as the characteristic value of the capacitance signal.
[0096] It can be understood that the amplitude of the current capacitance change trend signal at this time is less than the preset signal amplitude, and the amplitudes of the preset number of capacitance change trend signals thereafter are all less than the preset signal amplitude. In other words, the current capacitance change trend signal at this time is the starting signal for the capacitance change trend signal to reach a stable state.
[0097] Through a large number of experiments and data collection analysis, it is known that abnormal signals take longer to reach a stable signal value than normal signals, that is, the starting signal position of the capacitance change trend signal reaching a stable state is later. Therefore, the capacitance signal characteristic value is determined according to the size of the sampling number corresponding to the current capacitance change trend signal, so that the capacitance signal characteristic value can reflect the sampling point position, and the sampling point position before and after can be used as a basis for judging whether it is a normal signal or an abnormal signal.
[0098] It can be understood that in other embodiments, the step of determining the characteristic value of the capacitance signal according to the current capacitance change trend signal includes the step of: determining the sampling time corresponding to the current capacitance change trend signal as the characteristic value of the capacitance signal. Since the capacitance change trend signal is also arranged in time sequence, there is a difference between the current capacitance change trend signal of the normal signal and the abnormal signal when the current capacitance change trend signal reaches the current sampling point time under the preset signal amplitude. That is, the current capacitance change trend signal can also be determined as the characteristic value of the capacitance signal.
[0099] In this embodiment, the sampling quantity corresponding to the current capacitance change trend signal is determined as the capacitance signal characteristic value, so that the obtained capacitance signal characteristic value can characterize the difference between a normal signal and an abnormal signal, thereby improving the reliability of the capacitance signal characteristic value.
[0100] In an exemplary embodiment, Figure 8 As shown, step 108 includes step 808 and step 810:
[0101] Step 808: When the characteristic value of the capacitance signal is greater than the preset alarm threshold, it is determined that there are bubbles in the sample.
[0102] Step 810: When the characteristic value of the capacitance signal is less than or equal to the preset alarm threshold, it is determined that there are no bubbles in the sample.
[0103] The value of the preset alarm threshold is not unique, and can be a value determined by a large amount of experimental data. The type of the preset alarm threshold is also not unique, and can be determined according to the type of the characteristic value of the capacitance signal. For example, when the characteristic value of the capacitance signal is a quantity, the preset alarm threshold is also a quantity; when the characteristic value of the capacitance signal is time, the preset alarm threshold is also time.
[0104] Through a large number of experiments and data collection analysis, it is known that abnormal signals take longer to reach a stable signal value than normal signals, that is, the position of the starting signal of the capacitance change trend signal reaching a stable state is later. Therefore, when the characteristic value of the capacitance signal is greater than the preset alarm threshold, it means that the characteristic value of the capacitance signal is relatively large at this time, and it can be determined that there are bubbles in the sample. When the characteristic value of the capacitance signal is less than or equal to the preset alarm threshold, it means that the characteristic value of the capacitance signal is relatively small at this time, and it can be determined that there are no bubbles in the sample.
[0105] In this embodiment, when the characteristic value of the capacitance signal is greater than the preset alarm threshold, it is determined that there are bubbles in the sample. When the characteristic value of the capacitance signal is less than or equal to the preset alarm threshold, it is determined that there are no bubbles in the sample. According to the band-down relationship between the characteristic value of the capacitance signal and the preset alarm threshold, the detection of bubbles can be achieved, and the process is simple.
[0106] In order to better understand the above embodiment, a detailed explanation is given below in conjunction with a specific embodiment. The bubble detection method is based on the sample suction component of the analyzer, adopts the tip suction technology route, collects the liquid level detection capacitance signal curve based on the existing liquid level detection hardware equipment, performs time domain analysis of the capacitance signal of a single sample suction, extracts the bubble characteristics from the capacitance signal, and alarms for the bubble situation. In one embodiment, Fig. 9 As shown, the bubble detection method comprises the following steps:
[0107] Step 1: Original signal acquisition.
[0108] The full capacitance curve S1 of the liquid level detection module during the sample suction process is collected and explained with three signals, including normal signal 1, abnormal signal, and normal signal 2. Normal signal 1 and normal signal 2 are both signal curves under normal sample suction, which refers to the signal curve without bubbles. Fig.10 The whole process of sample suction is controlled by the motor, including the four steps of needle raising, needle moving, needle lowering and needle raising. Each step has a corresponding flag signal as a basis. Fig.10 In the specific example, normal signal 1, abnormal signal, and normal signal 2 are signals obtained by sampling the same sample three times. The normal signal 1 and the normal signal 2 have different trigger positions due to the change in liquid level; the abnormal signal is caused by the signal change caused by bubbles mixed in the collected sample.
[0109] Step 2: Baseline segment signal interception.
[0110] Extract the original baseline segment feature S2 of the capacitance curve S1 to obtain S3. Fig.11As shown in FIG. 1 , the baseline segment is defined as the capacitance signal of a specific interval (t0, t1), t0 is the signal point position returned after the liquid level detection detects the liquid level, representing the trigger position of the liquid level detection, and t1 is the signal point position where the detection needle starts and ends the detection during the entire detection process, representing the starting position of the sample suction needle. Fig.12 is the intercepted signal.
[0111] Step 3: Characteristic signal calculation.
[0112] Since the characteristics of signal S3 are not obvious, its characteristics need to be amplified. The specific steps are to perform signal differentiation after filtering S3 in the above step 2, that is, calculate the difference between the current signal and the previous signal, and filter the differential signal again to obtain the final characteristic signal S4, such as Fig.13 As shown. This calculation step mainly realizes the following functions: Complete the removal of the noise of the original signal, and eliminate the influence of burrs and miscellaneous peaks on the next calculation. Complete the calculation of the signal change trend. The specific method is differential signal calculation, which makes the change trend intuitive and prepares for the next calculation. Complete the noise removal of the differential signal, and eliminate the influence of burrs and miscellaneous peaks on the next calculation.
[0113] Step 4: Feature calculation.
[0114] The characteristics of the S4 signal are calculated, and a large amount of actual client data is collected and analyzed. It is found that the abnormal signal takes a longer time to reach a stable signal value than the normal signal, and the interference to the abnormal data when it reaches a stable state is the fluctuation of the signal amplitude.
[0115] In order to filter out abnormal signals, a threshold needs to be set to determine the time characteristics of its reaching a stable state, and the calculated signal amplitude is less than the preset signal amplitude T1 as the basis for its reaching a stable state.
[0116] At the same time, since the amplitude fluctuation may exist in multiple stages, a single amplitude fluctuation may cause the detection to be triggered in advance. Therefore, the signal feature points where the N signal amplitudes after the threshold T1 are all less than T1 are used as the final bubble judgment basis to exclude the influence of multiple fluctuations, such as Fig.13 As shown, the specific steps are as follows:
[0117] Step (1): Get the current signal amplitude at point i: Mi, and determine whether it is less than T1:
[0118] Di=Mi<T1
[0119] Step (2): If Di is false, then:
[0120] i=i+1
[0121] Then re-execute step (1);
[0122] Step (3) If Di is true, determine the amplitude of the subsequent N signals. If the subsequent N determination values are all true, obtain the characteristic value Z = i. If the subsequent N determination values are not all true, repeat step (2);
[0123] Di+j(j=1,2...N)=Mi+j<T1
[0124] j=j+1
[0125] The selected threshold value T1 and subsequent judgment points are specific values obtained by collecting and statistically analyzing a large amount of actual data.
[0126] Step 5: Status determination.
[0127] Based on the characteristic parameter Z obtained in step 4 above, an alarm is performed. If the current characteristic parameter Z>T2, an alarm is issued to indicate the presence of bubbles, otherwise no alarm is issued, where T2 is the alarm threshold. The threshold is determined through a large amount of experimental data.
[0128] The bubble detection method provided in this embodiment, based on the existing liquid level detection module, achieves the purpose of accurate judgment and alarm on the existence of bubbles through specific algorithm logic without adding additional sensors. It effectively avoids the instrument from issuing inaccurate clinical results, does not add additional hardware, effectively controls costs, and further reduces the risk of abnormal sample aspiration caused by bubbles.
[0129] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.
[0130] Based on the same inventive concept, the embodiment of the present application also provides a bubble detection device for implementing the bubble detection method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more bubble detection device embodiments provided below can refer to the limitations on the bubble detection method above, and will not be repeated here.
[0131] In an exemplary embodiment, Fig.14 As shown, a bubble detection device is provided, including: a signal acquisition module 1402, a signal change analysis module 1404, a signal feature determination module 1406 and a judgment module 1408, wherein:
[0132] The signal acquisition module 1402 is used to collect the capacitance signal of the liquid level detection module during the sample absorption process; the liquid level detection module is used to detect the liquid level of the sample;
[0133] The signal change analysis module 1404 is used to calculate the change trend of the capacitance signal and obtain a capacitance change trend signal;
[0134] A signal characteristic determination module 1406, configured to determine a capacitance signal characteristic value according to the capacitance change trend signal and a preset signal amplitude;
[0135] The judgment module 1408 is used to determine whether there are bubbles in the sample according to the characteristic value of the capacitance signal and the preset alarm threshold.
[0136] In an exemplary embodiment, the bubble detection device also includes a signal interception module, which is used to intercept the capacitance signal of the baseline segment in the capacitance signal after the signal acquisition module collects the capacitance signal of the liquid level detection module during the sample absorption process, and before the signal change analysis module calculates the change trend of the capacitance signal and obtains the capacitance change trend signal; the capacitance signal of the baseline segment includes the capacitance signal between the liquid level detection trigger position and the sample absorption needle starting position; the capacitance signal of the baseline segment is updated.
[0137] In an exemplary embodiment, the signal change analysis module is further used to perform differential signal calculation on the capacitance signal to obtain a capacitance change trend signal.
[0138] In an exemplary embodiment, the signal change analysis module is further used to filter the capacitance signal and then calculate the differential signal to obtain the differential signal; after filtering the differential signal, the capacitance change trend signal is obtained.
[0139] In an exemplary embodiment, the signal characteristic determination module is further used to determine the capacitance signal characteristic value according to the capacitance change trend signal whose amplitude is less than the preset signal amplitude.
[0140] In an exemplary embodiment, the signal characteristic determination module is also used to determine the capacitance signal characteristic value according to the current capacitance change trend signal when the amplitude of the current capacitance change trend signal is less than the preset signal amplitude and the amplitudes of a preset number of capacitance change trend signals after the current capacitance change trend signal are all less than the preset signal amplitude.
[0141] In an exemplary embodiment, the signal characteristic determination module is further configured to determine the number of samples corresponding to the current capacitance change trend signal as the capacitance signal characteristic value.
[0142] In an exemplary embodiment, the judgment module is also used to determine that bubbles exist in the sample when the characteristic value of the capacitance signal is greater than a preset alarm threshold; and to determine that bubbles do not exist in the sample when the characteristic value of the capacitance signal is less than or equal to the preset alarm threshold.
[0143] Each module in the above-mentioned bubble detection device can be implemented in whole or in part by software, hardware and a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module above.
[0144] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.
[0145] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.
[0146] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.
[0147] In one embodiment, an analyzer is provided, including a liquid level detection module and a controller, wherein the controller is connected to the liquid level detection module. The liquid level detection module is used to detect the liquid level of the sample, generate a capacitance signal and send it to the controller, and the controller is used to perform bubble detection according to the method of any of the above embodiments. The analyzer may be, for example, an in vitro diagnostic analyzer, and specifically, for example, a chemiluminescent immunoassay analyzer, a specific protein analyzer, a glycated hemoglobin analyzer, etc.
[0148] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.
[0149] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0150] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.
Claims
1. A bubble detection method, characterized in that: The method comprises: Collecting a capacitance signal of a liquid level detection module during the sample suction process; the liquid level detection module is used to detect the liquid level of the sample; Calculating the variation trend of the capacitance signal to obtain a capacitance variation trend signal; Determining a capacitance signal characteristic value according to the capacitance change trend signal and a preset signal amplitude; Whether bubbles exist in the sample is determined according to the characteristic value of the capacitance signal and a preset alarm threshold.
2. The method according to claim 1, characterized in that After collecting the capacitance signal of the liquid level detection module during the sample suction process and before calculating the change trend of the capacitance signal to obtain the capacitance change trend signal, the method further includes: In the capacitance signal, a capacitance signal of a baseline segment is intercepted; the capacitance signal of the baseline segment includes a capacitance signal between a liquid level detection trigger position and a sample suction needle starting position; The capacitance signal is updated using the capacitance signal of the baseline segment.
3. The method according to claim 1, characterized in that The calculating the variation trend of the capacitance signal to obtain a capacitance variation trend signal includes: Perform differential signal calculation on the capacitance signal to obtain the capacitance change trend signal.
4. The method according to claim 3, characterized in that The performing differential signal calculation on the capacitance signal to obtain the capacitance change trend signal includes: After filtering the capacitance signal, performing differential signal calculation to obtain a differential signal; After filtering the differential signal, the capacitance change trend signal is obtained.
5. The method according to claim 1, characterized in that The determining of the capacitance signal characteristic value according to the capacitance change trend signal and the preset signal amplitude includes: The capacitance signal characteristic value is determined according to a capacitance change trend signal whose amplitude is smaller than the preset signal amplitude.
6. The method according to claim 5, characterized in that The determining the capacitance signal characteristic value according to the capacitance change trend signal having an amplitude less than the preset signal amplitude includes: When the amplitude of the current capacitance change trend signal is smaller than the preset signal amplitude, and the amplitudes of a preset number of capacitance change trend signals after the current capacitance change trend signal are all smaller than the preset signal amplitude, the capacitance signal characteristic value is determined according to the current capacitance change trend signal.
7. The method according to claim 6, characterized in that The determining the capacitance signal characteristic value according to the current capacitance change trend signal includes: The sampling quantity corresponding to the current capacitance change trend signal is determined as the capacitance signal characteristic value.
8. The method according to claim 1, characterized in that The determining whether there are bubbles in the sample according to the characteristic value of the capacitance signal and a preset alarm threshold comprises: When the characteristic value of the capacitance signal is greater than the preset alarm threshold, determining that bubbles exist in the sample; When the characteristic value of the capacitance signal is less than or equal to the preset alarm threshold, it is determined that no bubbles exist in the sample.
9. A bubble detection device, characterized in that: The device comprises: A signal acquisition module, used to collect the capacitance signal of the liquid level detection module during the sample aspiration process; the liquid level detection module is used to detect the liquid level of the sample; A signal change analysis module, used to calculate the change trend of the capacitance signal and obtain a capacitance change trend signal; A signal characteristic determination module, used to determine a capacitance signal characteristic value according to the capacitance change trend signal and a preset signal amplitude; The judgment module is used to determine whether there are bubbles in the sample according to the characteristic value of the capacitance signal and a preset alarm threshold.
10. An analyzer, characterized in that: It comprises a liquid level detection module and a controller, wherein the controller is connected to the liquid level detection module; The liquid level detection module is used to detect the liquid level of the sample, generate a capacitance signal and send it to the controller, and the controller is used to perform bubble detection according to the method according to any one of claims 1-8.